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Record W4210378879 · doi:10.1190/int-2021-0152.1

Evaluation method of hydrocarbon yield of source rocks in open, semiopen, and closed systems: A case study on the K1qn Formation, northern Songliao Basin, China

2022· article· en· W4210378879 on OpenAlexaff
Wenguang Wang, Min Wang, Shuangfang Lu, Chengyan Lin, Min Zheng

Bibliographic record

VenueInterpretation · 2022
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsPetro-Canada
FundersNational Natural Science Foundation of China
KeywordsSource rockHydrocarbonGeologyKerogenYield (engineering)CrackingFossil fuelBasin modellingStructural basinPetroleum engineeringMineralogyGeochemistryChemistryGeomorphologyEngineeringThermodynamicsWaste management

Abstract

fetched live from OpenAlex

Abstract Hydrocarbon yield of source rocks is an important parameter in the evaluation of oil and gas resources, and its value determines the potential of conventional and unconventional oil and gas resources. There is no oil cracking into gas in the thermal pyrolysis experiment data of an open system, whereas kerogen cracking into oil in a closed system is involved in the calculation of oil cracking into gas. However, most source rocks in sedimentary basins are a process of hydrocarbon generation and hydrocarbon expulsion, which could lead to insufficient understanding of hydrocarbon yield of source rocks. Based on the multiple thermal pyrolysis experiment data, three hydrocarbon generation kinetic models, and actual geologic data (burial history, thermal history, and hydrocarbon generation threshold), we established the evaluation method and chart of hydrocarbon yield of source rocks under open, semiopen, and closed systems by using the hydrocarbon generation kinetics method. The concept of degree of openness was proposed. From a closed system to an open system, the degree of openness increases gradually, and its value changes from 0 to 1. Taking the K1qn Formation in the northern Songliao Basin as an example, the hydrocarbon expulsion efficiency of the K1qn Formation source rock is approximately 70%, and it can be approximated as the degree of openness. Based on our method for evaluating hydrocarbon yield of source rocks, the charts of hydrocarbon yield of source rocks under open system, semiopen system with a degree of openness of 0.7, and closed system of the K1qn Formation in the northern Songliao Basin were established. The oil and gas yields of the K1qn Formation source rocks in a semiopen system with a degree of openness of 0.7 are approximately 540 and 105 mgHC/gTOC at a burial depth of 2000 m, respectively. Our results indicate that the hydrocarbon yield of source rocks in a semiopen system is closer to the hydrocarbon yield of source rocks under geologic condition. We use the thermal pyrolysis experiment data, hydrocarbon generation kinetics model, and geologic data to propose a very valuable evaluation method of hydrocarbon yield of source rock, which has a solid theoretical basis and strong applicability.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.396

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.290
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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